On Efficient External-Memory Triangle Listing

被引:5
|
作者
Cui, Yi [1 ]
Xiao, Di [1 ]
Loguinov, Dmitri [1 ]
机构
[1] Texas A&M Univ, Dept Comp Sci & Engn, College Stn, TX 77843 USA
关键词
Triangle listing; external memory; graph algorithms; GRAPHS; INTERSECTION;
D O I
10.1109/TKDE.2018.2858820
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Discovering triangles in large graphs is a well-studied area; however, both external-memory performance of existing methods and our understanding of the complexity involved leave much room for improvement. To shed light on this problem, we first generalize the existing in-memory algorithms into a single framework of 18 triangle-search techniques. We then develop a novel external-memory approach, which we call Pruned Companion Files (PCF), that supports operation of all 18 algorithms, while significantly reducing I/O compared to the common methods in this area. After finding the best node-traversal order, we build an implementation around it using SIMD instructions for list intersection and PCF for I/O. This method runs 5-10 times faster than the available implementations and exhibits orders of magnitude less I/O. In one of our graphs, the program finds 1 trillion triangles in 237 seconds using a desktop CPU.
引用
收藏
页码:1555 / 1568
页数:14
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